1. Field of the Invention
The present invention relates in general to a model-based object classification and target recognition and in particular to a structure and the execution of models for object classification and localization.
2. Discussion of Background Information
All previously known methods from the prior art which use explicit geometry models for matching extract only few features at the same time from the input data. There are several reasons for this.
For one reason, it is difficult to fuse different features so that identical benchmark values have an identical meaning. For another reason, there are purely practical reasons that will be explained in more detail below.
Furthermore, the rules of when a feature of a model is to be checked, are either just as firmly programmed in as the feature itself or they are determined from the geometry of the object.
The previously known systems, thus also those of D. G. Lowe in Fitting Parametrized Three-Dimensional Models to Images, IEEE Transact. on Pattern Analysis and Machine Intelligence, Vol. 13. No. 5, 1991, those of L. Stephan et al. in Portable, scalable architecture for model-based FLIR ATR and SAR/FLIR fusion, Proc. of SPIE, Vol. 0.3718, Automatic Target Recognition IX, August 1999 and those described in EP-A-622 750 have in general a fixed arrangement of the image processing and in particular a fixed arrangement of the preprocessing.
According to these known systems, the image is read in, then it is preprocessed and subsequently matching is carried out. This means in the known systems that either all preprocessing whose results are contained in any model has to be carried out or firmly implemented tests have to be carried out that avoid this preprocessing.
A method for classifying documents, in particular bank notes, is known from DE 10045360 A1 in which a document to be classified is classified in a certain class on the basis of features with higher significance. In this connection the document is subdivided into individual feature areas which are preferably square. Among these feature areas additionally selected feature areas are formed which are used for determining the class. The establishment of these selected feature areas thereby occurs in a separate adaptation process before classification on the basis of reference documents. In this connection the selected feature areas have a higher significance, i.e. deciding force, than the other feature areas.